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Associate Data Scientist - Algorithms and Data Insights

Stamford, Connecticut

Job Description:

What makes Gartner a GREAT fit for you? When you join Gartner, you’ll be part of a fast-growing team that helps the world become smarter and more connected. We’re the world’s leading research and advisory company, achieving consistent double-digit growth by steering clients toward the right decisions with business and technology insights they can’t find anywhere else. Our associates enjoy a collaborative work environment, exceptional training and career development — as well as unlimited growth opportunities. If you like working with a curious, supportive, high-performing team, Gartner is the place for you.

This is a unique opportunity to join our fast-growing Data Science team and work with a group of data scientists and data engineers to drive significant business impact. Your team focuses on driving client engagement. Engaging clients with the right piece of advice is core to our economics, among varies initiatives from different angles, data science is one of the most impactful yet scalable levers. Team owns algorithm varies from website recommendation logics, core search engine algorithms and varies machine learning and NLP models related to search, content and user modeling to outbound email logics, as well as the infrastructure that powers those algorithms such as parallel computing environment, data lake and pipelines.

The  Algorithms and Data Insights team manages the end to end process of turning innovative ideas into data models and systems that drive significant business outcome. Our work involves generating ideas, creating business cases, and quickly developing models and to test in real world scenarios. The ideal candidate would be a champion of applying data science to improve client experiences. They would be willing to iterate quickly during model development, but be capable of building more complex algorithms when necessary.

Your Responsibilities:

Given the broad areas that we are responsible for, you will likely start in one domain but quickly get involved in other domains. A few potential projects include:

  • Applying Natural Language Processing to improve our ability to synthesize client search queries so we offer best content based on their intent
  • Using machine learning to develop self-correcting algorithms to improve our recommendation targeting in Email
  • Using predictive modeling to develop forward-looking projections of client retention and purchasing.
  • Using statistical analysis to evaluate and improve existing algorithms
  • Conceptually mapping cause and effect relationships to statistical models to develop a robust understanding of business drivers


  • 1-3 years hands-on experience building predictive models, recommendation systems, or NLP/text mining tools.
  • Familiar with the  foundational approaches to the major data science disciplines, such as data preparation, advanced statistics, machine learning, simulation, and natural language processing
  • Practical, intuitive problem solver with a demonstrated ability to translate business objectives into actionable data science tasks and translate quantitative analysis into actionable business strategies
  • Connections to the recommendations and / or information retrieval academic community
  • Experience and proficiency with various programming languages (e.g., Python), machine learning tools (e.g., scikit-learn), statistical packages (e.g., Scipy), SQL/relational databases (e.g., Oracle) and NoSQL databass (e.g., MongoDB, graph database), Linux and shell scripting
  • Masters in a quantitative research field (e.g., Computer Science, Electrical Engineering, Applied Mathematics, Physics, Neuroscience etc.). PhD preferred.

Job Requisition ID:34773

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